Anthropic may build its own AI chips amid rising demand and supply crunch
Follow UsAnthropic is exploring the development of its own AI chips to reduce reliance on external suppliers amid rising demand and hardware shortages.
Company currently depends on Nvidia, Google, and Broadcom for AI hardware
In-house chip plans are still early-stage with no final design or dedicated team yet
Anthropic is again making headlines and this time it is for something new. As per the reports, the AI startup is reportedly considering designing its own AI chips. The company is reportedly aiming to reduce its dependence on third-party hardware providers and address growing shortages. This comes at a time when demand for high-performance AI infrastructure continues to surge globally.
SurveyAccording to a report by Reuters and The Information, the company is evaluating the feasibility of developing in-house chips, although the effort is still in its early stages with no final design or dedicated engineering team in place yet.
At present, Anthropic relies on a mix of hardware from big players like Nvidia, Google and Broadcom. It also uses cloud-based chips such as Amazon’s Trainium and Inferentia processors, along with Google’s tensor processing units (TPUs) for training and running its AI models, including the Claude chatbot. However, with AI adoption, access to such resources is getting difficult.
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Anthropic has already partnered with Google and Broadcom to co-develop the TPU infrastructure to expand its AI computing capacity in the United States. While the company is expanding its strategic partnerships, this new in-house chip development shows the pressure on AI firms to secure dedicated resources. And for established chipmakers like Nvidia, this can be a gradual shift as customers look to reduce reliance on external suppliers.
As per the reports, the industry estimates suggest that development costs can exceed $500 million. Not only that, but the company will also need specialised talent and long timelines for design, testing and large-scale manufacturing. But for now, these ambitions remain exploratory.
